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Monday, 19 October 2015

Project Viability – a cybernetics approach, part 1

A lot has been said and written about why projects succeed
and why they fail. Surveys are carried out and analyses published. And whilst
many common themes emerge when you read about them, not a lot seems to change. It
leaves me wondering whether we’re on quite the right track when we ask about
project success or failure. I wonder of we should ask about project
“viability”. Let me explain…

In 1953 the brilliant systems theorist and cybernetics expert, W.
Ross Ashby noted: “Only variation can force variation down”[1],
which he published in his 1956 book An
Introduction to Cybernetics as The Law of Requisite Variety: “[only]
variety can destroy variety”[2]. To put it another way, “control can be
obtained only if the variety of the controller … is at least as great as the
situation to be controlled”[3].

Variety is the number of distinguishable items or states[4],
so if you’re in a situation where there are 100 possible states, you can only
effectively deal with it if you can mimic those 100 states yourself: you have
to have the same variety capacity, otherwise you simply can’t deal with all the
variety you encounter. Of course in reality the amount of variety we encounter
is far greater than this: possibly almost infinite. Stafford Beer, another
brilliant cyberneticist, took Ashby’s work and built a model for how to deal
effectively with variety, which he called the Viable Systems Model (VSM: of
which more later). Basically, Beer stated that in real life it’s impossible to
match variety 100%, so the controlling system needs to be able to deal with
variety in such a way that it remains viable as a system (i.e. it can survive).
He called this requisite variety.

What has this got to do with projects and project
management? Putting this into project management terms, a project can only
successfully deliver if it can deal with the variety it encounters effectively.

If this sounds like common sense, so it is. But how do you do that. How do you cope with variety
effectively given that you can’t deal with it 100%? Beer’s VSM is all about
having a model that can understand enough about the variety to deal with it
effectively, without being flooded with all the variety that there is. And to
do that you need some kind of filter (Beer calls this an attenuator) so that
the incoming variety is reduced. You also need an amplifier on the output side
so that your output isn’t just lost in the noise of the variety that’s out
there.

To use a very simple
human analogy: we filter out background noise in a crowded room so we can
listen to the person we’re speaking to. How does our attenuator work? We make
sure we are looking directly at the person we’re speaking to so we can pick up
visual signals to help us filter auditory input. They help by amplifying their
output to help you focus on it, for example by saying your name to help you
“pin” their speech. They might write something down or draw a diagram. And so on.

So now we have a basic model of how to deal effectively with
variety, as illustrated here[5].

However there are four problems that I believe commonly occur in projects that
cause this loop to fail somewhere:

1. Putting attenuation in the right place

One of the biggest problems with projects is getting the
attenuator and the amplifier right, and there are two issues here. The first is
getting them on the right side of the loop – as shown in the diagram. Often we
do the reverse and have the amplifier on the incoming route – making our
ability to deal with variety worse, not better; and the we attenuate the
output. Let me give a very simple example. We gather requirements for a system.
An awful lot of them. We talk to lots of stakeholders to get their points of
view. We get a lot of those too. Some of them are in conflict. But we strive to
“gather all the requirements” (amplifier). Out of this welter of
incoming variety we create a product of some sort, but we fail to engage fully
with the customer (attenuator) so it’s never fully deployed. The recent article
by Mark Phillips in PMT had a great example of this with a development project
that failed because the scope kept increasing (amplified input)[6].

So the first thing to do is make sure you have attenuation in place on the
input side of the project. Next we’ll look at how this should be configured so
you cut out what isn’t necessary but don’t cut out important stuff.

2. Getting attenuation right

Assuming we are attenuating the input, how do we do it
correctly? In DSDM Atern the use of MoSCoW[7] is recommended to prioritise requirements: MoSCoW can be an effective
attenuator if use correctly. However, in spite of tools like MoSCoW and
methodologies like DSDM Atern, we still seem to get it wrong too often. This is
sometimes because the attenuation is not effective (e.g. people don’t
prioritise effectively: everything is a “must have”).

Another attenuator we don’t use effectively enough is
stakeholder management. A good stakeholder analysis will reveal those
stakeholders who will have a lot of power and influence over the project, and
also those who may not be so powerful but will be key users. We can then
effectively ignore all other stakeholders in terms of getting input: we don’t need
to know what they want!

Sometimes the attenuation works fine and still the project
fails! This can be cause amplification isn’t working properly, as we’ll see
next.

3. Getting amplification right

A third problem is ensuring that the output is properly
amplified assuming the product is completed effectively and the input side of
the loop is OK. A typical example of poor output amplification is when a product
is successfully delivered – and then is either not adopted or not effectively
adopted. This is very common in IT systems implementation where the grand new
system ends up causing more problems than it solves because staff don’t like it
and find workarounds. Often there is insufficient work done to prepare people
for the new product so their expectations are misaligned with what is
delivered. This is poor amplification on the output loop.

Typically we use communication methods such as emails and
posters and web sites. But these can get lost in the noise: they aren’t effective
amplifiers. We need to explore what the users will take notice of and use
those. This will differ from one situation to the next. One very successful
project I was involved with, where schoolchildren were the intended users, created
a piece of live, interactive drama that was delivered to the schools, and this engaged
attention and got a good result.

4. Dealing with internal variety

The diagram also includes the box on the right side of the
loop – the actual project itself. Will the project deliver its products
effectively, even if we get attenuation right? Often we fail in this too, and a
big contributor is that we don’t treat the project as a system. Beer’s Viable
Systems Model is a generally applicable model for the cybernetic organisation
of how a system should work. Projects are systems, so the model can be applied
to projects as well. I have written a series on this topic, the first part of
which you can find here.

My next article in this series will look at these the first two problems in a little more detail, applying the cybernetic principles of Beer. It will attempt to show how projects might be run on better lines. If at the end of reading this you think it’s common sense; then yes it is. But ‘hindsight explains the injury that foresight would have prevented’[8]
[1] See the Ashby digital archive, and page 4659 of his Journal, available online at http://www.rossashby.info/index.html [Accessed 19 October 2015]